{"url":"/dataset/simply-clevr","name":"simply-CLEVR","full_name":null,"description_markdown":"The **simply-CLEVR** dataset aims to provide a benchmark dataset that can be used for transparent quantitative evaluation of explanation methods (aka heatmaps/XAI methods).\nIt is made of simple Visual Question Answering (VQA) questions, which are derived from the original CLEVR task, and where each question is accompanied by two Ground Truth Masks that serve as a basis for evaluating explanations on the input image.\n\nSource: [https://github.com/ahmedmagdiosman/simply-clevr-dataset](https://github.com/ahmedmagdiosman/simply-clevr-dataset)\nImage Source: [https://github.com/ahmedmagdiosman/simply-clevr-dataset](https://github.com/ahmedmagdiosman/simply-clevr-dataset)","description_withheld":null,"homepage":"https://github.com/ahmedmagdiosman/simply-clevr-dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/towards-ground-truth-evaluation-of-visual","title":"Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI","first_author":"Leila Arras","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Visual Question Answering (VQA)","url":"/task/visual-question-answering","datasets_with_task":"/datasets/task/visual-question-answering"},{"name":"Feature Importance","url":"/task/feature-importance","datasets_with_task":"/datasets/task/feature-importance"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["simply-CLEVR"],"data_loaders":[{"repo":"https://github.com/ahmedmagdiosman/simply-clevr-dataset","url":"https://github.com/ahmedmagdiosman/simply-clevr-dataset","frameworks":[]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}